Abstract Background The application of Big Data analytics in healthcare has immense
potential for improving the quality of care, reducing waste and error, and reducing the cost of …

Mobile health (m‐health) is the term of monitoring the health using mobile phones and
patient monitoring devices etc. It has been often deemed as the substantial breakthrough in …

Manufacturing and service organisations improve their processes on a continuous basis to
have better operational performance. They use lean six sigma (LSS) projects for process …

Dünyadaki veri hacmi ve veri çeşitliliği, insanlık tarihinde daha önce hiç görülmediği hızda
artmaktadır. İnternet teknolojilerinin ve sosyal medyanın hayatımızın her evresine ve hatta …

Big data analytics are gaining popularity in medical engineering and healthcare use cases.
Stakeholders are finding big data analytics reduce medical costs and personalise medical …

Internet of Things (IoT)-based Healthcare services, which are becoming more widespread
today, continuously generate huge amounts of data which is often called big data. Due to the …

Over the past decade, data recorded (due to digitization) in healthcare sectors have
continued to increase, intriguing the thought about big data in healthcare. There already …

The osmotic computing paradigm sets out the principles and algorithms for simplifying the
deployment of Internet of Things (IoT) applications in integrated edge-cloud environments …

Abstract Background and objectives Bidirectional Encoder Representations from
Transformers (BERT) word embedding models have been successfully used for many …

Deep learning (DL) models typically require large-scale, balanced training data to be robust,
generalizable, and effective in the context of healthcare. This has been a major issue for …